Text Classification
Transformers
Safetensors
modernbert
sentiment-analysis
multilingual
restaurants
5-star
text-embeddings-inference
Instructions to use Festooned/Multilingual-Restaurant-Reviews-Sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Festooned/Multilingual-Restaurant-Reviews-Sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Festooned/Multilingual-Restaurant-Reviews-Sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Festooned/Multilingual-Restaurant-Reviews-Sentiment") model = AutoModelForSequenceClassification.from_pretrained("Festooned/Multilingual-Restaurant-Reviews-Sentiment") - Notebooks
- Google Colab
- Kaggle